Handles creating, reading and updating training materials.

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            "name": "Chip-seq: Discovering motifs in peaks with RSAT",
            "description": "Read mapping: from raw reads to aligned reads.\nPeak calling: from aligned reads to regions/peaks of high read density.\nChIP-seq annotation\nIdentification of genes related to the peaks.\nProfiles of ChIP-seq reads around reference points (TSS, histone marks,).\nFunctional enrichment of the genes related to the peaks.\n\n",
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            "id": 86,
            "name": "Gut metagenomics in cardiometabolic diseases",
            "description": "Cardio-metabolic and Nutrition-related diseases (CMDs) represent an enormous burden for health care. They are characterized by very heterogeneous phenotypes progressing with time. It is virtually impossible to predict who will or will not develop cardiovascular comorbidities. There is a clear need to intervene earlier in the natural cycle of the disease, before irreversible tissue damages develop. Predictive tools still remain elusive and environmental factors (food, nutrition, physical activity and psychosocial factors) play major roles in the development of these interrelated pathologies. Poor nutritional environment and lifestyle also promote health deterioration resulting in CMD progression. In the last few years, the characterization of the gut microbiome (i.e. collective bacteria genome) and gut-derived molecules (i.e. metabolites, lipids, inflammatory molecules) has opened up new avenues for the generation of fundamental knowledge regarding putative shared pathways in CMD. The gut microbiome is likely to have an even greater impact than genetic factors given its close relationship with environmental factors. In metabolic disorders, the discoveries that low bacterial gene richness associates with cardiovascular risks stimulate encourage these developments. Due to the complexity of the gut microbiome, and its interactions with human (host) metabolism as well as with the immune system, it is only through integrative analyses where metabolic network models are used as scaffold for analysis that it will be possible to identify markers and shared pathways, which will contribute to improve patient stratification and develop new modes of patient care.\n",
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            "id": 49,
            "name": "Development in Galaxy",
            "description": "Galaxy is an open-source project. Everyone can contribute to its development with core Galaxy development, integration of softwares in Galaxy environment, ... Here, you will find some materials to learn how to contribute to Galaxy project.\n",
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            "id": 22,
            "name": "CWL support in Galaxy",
            "description": "\n \n\nCWL support in Galaxy\n \n",
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            "id": 70,
            "name": "Revealing and analyzing microbial networks: from topology to functional behaviors",
            "description": "Understanding the interactions between microbial communities and their environment well enough to be able to predict diversity on the basis of physicochemical parameters is a fundamental pursuit of microbial ecology that still eludes us. However, modeling microbial communities is a complicated task, because (i) communities are complex, (ii) most are described qualitatively, and (iii) quantitative understanding of the way communities interacts with their surroundings remains incomplete. Within this seminar, we will illustrate two complementary approaches that aim to overcome these points in different manners.\n",
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            "doi": null,
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            "id": 45,
            "name": "Galaxy Visualisation - Slides",
            "description": "Questions\n\n\n\tHow can visualization plugins benefit science?\n\n\n\nObjectives\n\n\n\tImplement a first Galaxy visualization\n\tUnderstand the client side vs. server side principle\n\n",
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            "doi": null,
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            "dateCreation": "2017-01-18",
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            "id": 60,
            "name": "Differential analysis of RNA-Seq data",
            "description": "Design, describe, explore and model\n",
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            "id": 105,
            "name": "Exploring Microscope Platform",
            "description": "\n \n\nHow to use the Microscope Platform to annotate and analyze microbial genomes.\n \n",
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            "doi": null,
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            "topics": [],
            "keywords": [
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                "Annotation",
                "Sequence analysis",
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                "Metabolomics"
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            "id": 75,
            "name": "Fast filtering, mapping and assembly of 16S ribosomal RNA",
            "description": "The application of next-generation sequencing technologies to RNA or DNA directly extracted from a community of organisms yields a mixture of nucleotide fragments. The task to distinguish amongst these and to further categorize the families of ribosomal RNAs (or any other given marker) is an important step for examining the phylogenetic classification of the constituting species. In this perspective, we have developed  a complete bioinformatics suite, called MATAM, capable of handling large sets of  reads in a fast and accurate way. MATAM covers all steps of the analysis, from the identification of reads of interest in the raw sequencing data to the reconstruction of the  full-length sequences of the marker and alignment to a reference database for taxonomic assignment. Part of MATAM is based on the SortMeRNA software, also developed by the team.\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_6/Fast_filtering_mapping_and_assembly_of_16S_rRNA/scormcontent/index.html",
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            "dateCreation": "2016-12-16",
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        {
            "id": 124,
            "name": "Snakemake tutorial: Gene regulation",
            "description": "Workflow 1: Rules and targets\nWorkflow 2: Introducing wildcards\nWorkflow 3: Keywords\nWorkflow 4: Combining rules\nWorkflow 5: Configuration file\nWorkflow 6: Separated files\n",
            "communities": [],
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            "doi": null,
            "fileLocation": "http://gene-regulation.readthedocs.io/en/latest/snakemake.html",
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            "dateCreation": "2016-04-13",
            "dateUpdate": null,
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            "id": 43,
            "name": "Galaxy Interactive Tour",
            "description": "Questions\nWhat is a Galaxy Interactive Tour?\nHow to create a Galaxy Interactive Tour?\nObjectives\nDiscover what is a Galaxy Interactive Tour\nBe able to create a Galaxy Interactive Tour\nBe able to add a Galaxy Interactive Tour in a Galaxy instance\n",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "http://galaxyproject.github.io/training-material/Dev-Corner/slides/interactive_tour.html",
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            "dateCreation": "2017-01-18",
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        {
            "id": 3,
            "name": "Transfer of Research Assets between FAIRDOM SEEKs",
            "description": "\n \n\nTransfer of Research Assets between FAIRDOM SEEKs\n \n",
            "communities": [],
            "elixirPlatforms": [],
            "doi": null,
            "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/transfer-of-research_9014/scormcontent/index.html",
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            "topics": [],
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            "dateCreation": "2019-03-21",
            "dateUpdate": null,
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        {
            "id": 61,
            "name": "Differential gene expression analysis : Practical part",
            "description": "RNA-seq: Differential gene expression analysis practical session\n",
            "communities": [],
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/R01b_EBA2016_TP_RNA-seq.pdf",
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            "topics": [],
            "keywords": [
                "genomics",
                "RNA-seq"
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            "providedBy": [],
            "dateCreation": "2016-11-22",
            "dateUpdate": null,
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        {
            "id": 87,
            "name": "Deciphering the human intestinal tract microbiome using metagenomic computational methods",
            "description": "In 2010, the MetaHIT consortium published a 3.3M microbiota gene catalog generated by whole genome shotgun metagenomic sequencing, representing a mixture of bacteria, archaea, parasites and viruses coming from 124 human stool metagenomic samples [Qin et al, Nature 2010].\nHowever most of the genes were fragmented, taxonomically and functionally unknown, making it difficult to define and select biomarkers of interest for genome-wide association studies.\nSince that, this human gene catalog was improved multiple times, with the last update by [Li et al, Nature Biotechnology, 2014], which generated a 10M gene catalog using more than 1000 metagenomic samples and including some prevalent human microbe genome available at that time. Along with the catalog update, the scientific community developed new tools to challenge the complexity of this dataset and provided new ways to assemble, annotate, quantify and classify the genes coming from these catalogs.\nIn this talk we will discuss the main approaches related to the computational treatment of the different gene catalog other the time, illustrated by the different papers that deciphered step by step the hidden information of our microbiota and his link with our health.\n",
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            "doi": null,
            "fileLocation": "http://www.france-bioinformatique.fr/sites/default/files/videos/scorms/metagenomics16/session_1/Deciphering_the_human_intestinal_tract_microbiome_using_metagenomic_computational_methods/scormcontent/index.html",
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            "dateCreation": "2016-12-15",
            "dateUpdate": null,
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            "id": 14,
            "name": "Galaxy training material improvement and extension",
            "description": "\n \n\nGalaxy training material improvement and extension\n \n",
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            "doi": null,
            "fileLocation": "http://ressources.france-bioinformatique.fr/sites/default/files/videos/scorms/galaxy-training-material_6300/scormcontent/index.html",
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            "id": 121,
            "name": "The IFB cloud for bioinformatics",
            "description": "\n\tPractical work to introduce basic and advanced usage of the IFB cloud\nHowto launch virtual machines\nManaging your data in the cloud ;\nHowto to connect to your VMS (SSH, web, remote desktop)\nPersonalizing your VMs (approver, galaxy, docker)\n\n",
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            "doi": null,
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            "keywords": [
                "Cloud Computing",
                "Virtual machine"
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            "dateCreation": "2016-06-01",
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            "id": 35,
            "name": "Defining and importing genomes, Data Managers into Galaxy",
            "description": "Intro to built in datasets\nBuilt in data hierarchy\nSome problems\nData Managers\n",
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            "doi": null,
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            "dateCreation": "2017-01-19",
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            "id": 63,
            "name": "Variant Filtering",
            "description": "Use cases:\nExtact a subset of variants\nCombine variants from several analysis\n\nCompare obtained variants from several data types\n\n\nIdentify new variants compare to a reference list\n\n\nApply specific filters for Chip Design\n\n",
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            "doi": null,
            "fileLocation": "http://ecole-bioinfo-aviesan.sb-roscoff.fr/sites/ecole-bioinfo-aviesan.sb-roscoff.fr/files/files/FiltrageVariantNLapaluRoscoff2015.pdf",
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            "id": 9,
            "name": "OmicsPath: Finding Relevant omics datasets using pathway information",
            "description": "\n \n\nOmicsPath: Finding Relevant omics datasets using pathway information\n \n",
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            "doi": null,
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            "dateCreation": "2019-03-21",
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            "id": 118,
            "name": "Chip-seq: Introduction to the Workshop",
            "description": "Data visualization, quality control, normalization & peak calling\nPeak annotation\nFrom peaks to motifs\n",
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            "fileLocation": "http://dputhier.github.io/EBA_2015_ChIP-Seq/slides/chipseq_CarlHerrmann_Roscoff2015.pdf",
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